Research Fellow (Traffic Management Project)

National University of Singapore; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A leading research university in Singapore is seeking a Postdoctoral Fellow for its Traffic Management Project. The role involves developing a data-driven traffic simulation model and requires a Ph.D. in Traffic Engineering or Computer Science. Candidates should be proficient in C++ and Python, and familiar with traffic systems and modelling. This position offers a unique opportunity to work on impactful traffic incident analysis and management frameworks.

Qualifications

• Ph.D holders in Traffic Engineering, Computer Science or related fields.
• Familiarity with traffic systems and simulation.
• Proficiency in programming languages like C++ and Python.

Responsibilities

• Work on the Traffic Management Project utilizing data-driven analytics.
• Design and develop data-driven traffic simulation models.
• Collaborate with transport engineering and data science teams.

Skills

C++

Python

Data modelling and collection

Traffic systems

Traffic modelling and simulation

Agent-based systems

Human behaviour models

Education

Ph.D in Traffic Engineering/Computer Science or related degree

Job description

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

Job Description

Applications are sought for a Postdoctoral Fellow to work on a Traffic Management Project. The project is primarily focused on applying data-driven analytics and simulation for Traffic Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost.

This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended outcomes will be an innovative incident analysis and management framework synergising traffic data analytics and traffic simulation modelling as well as its key enabling techniques and prototype systems. This will significantly help mitigate incident impacts on daily commuters.

This project is a National Research Foundation (NRF)/Australian Research Council (ARC) collaborative project between National University of Singapore (NUS), Nanyang Technological University (NTU), and several partners in Australia, namely Swinburne University of Technology (SUT), Melbourne, and University of Technology (UTS), Sydney. The appointed postdoc and research assistant will jointly work on the design and development of a data-driven traffic simulation model that combines data-driven and simulation-based techniques, so that it can support multi-level, multi-modal and on-demand traffic simulation.

Qualifications

• Postdoctoral candidates should have a Ph.D in Traffic Engineering/Computer Science or related degree, and be familiar with
• Data modelling and collection
• Traffic Systems / Traffic Modelling and simulation
• Agent-based systems & simulation / Experience in Human Behaviour models will be useful
• Candidates should be proficient in C++, Python, and preferably have experience with Traffic Simulation models or packages.